-Question answering with intelligent knowledge management of biomedical texts and analysis of rhetoric relations in the AROMA system is presented. The development of the AROMA system aims at the creation of an intelligent tool for the support of the discovery and adaptation of biomedical models based on data extracted from natural language texts. The system operation includes three main functio...

In this survey paper, we discuss biomedical ontologies and major text mining techniques applied to biomedicine and healthcare. Biomedical ontologies such as UMLS are currently being adopted in text mining approaches because they provide domain knowledge for text mining approaches. In addition, biomedical ontologies enable us to resolve many linguistic problems when text mining approaches handle...

BACKGROUND There is currently a gap between the rich and expressive collection of published biomedical ontologies, and the natural language expression of biomedical papers consumed on a daily basis by scientific researchers. The purpose of this paper is to provide an open, shareable structure for dynamic integration of biomedical domain ontologies with the scientific document, in the form of an...

We propose a biomedical event extraction system, HVS-BioEvent, which employs the hidden vector state (HVS) model for semantic parsing. Biomedical events extraction needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In HVS-BioEvent, we further propose novel machine learning approaches for event trigger word ident...

We present a named-entity recognition (NER) system for parallel multilingual text. Our system handles three languages (i.e., English, French, and Spanish) and is tailored to the biomedical domain. For each language, we design a supervised knowledge-based CRF model with rich biomedical and general domain information. We use the sentence alignment of the parallel corpora, the word alignment gener...

As new high-throughput technologies have created an explosion of biomedical literature, there arises a pressing need for automatic information extraction from the literature bank. To this end, biomedical named entity recognition (NER) from natural language text is indispensable. Current NER approaches include: dictionary based, rule based, or machine learning based. Since there is no consolidat...

Large biomedical projects often include workflows running across institutional borders. In these workflows, data describing biomedical entities, such as patients, bio-materials but also processes itself, is typically produced, modified and analyzed at different locations and by several systems. Therefore, both tracking entities within inter-organizational workflows and data integration are ofte...

New low modulus β-type titanium alloys for biomedical applications are still currently being developed. Strong and enduring β-type titanium alloy with a low Young's modulus are being investigated. A low modulus has been proved to be effective in inhibiting bone atrophy, leading to good bone remodeling in a bone fracture model in the rabbit tibia. Very recently β-type titanium alloys with a self...

Is biomedical informatics a science or a profession? This question has been asked of many members in the biomedical informatics community, yet we still lack a response that galvanizes our community. We debate the issues over lunch. We create long, multi-threaded e-mail discussions, we write papers on the topic, and still we aren't able to convince ourselves-let alone the rest of the scientific ...